The Data Interpretation Gap

Data is everywhere, but insight is rare. This session explores how meaning is constructed through three interconnected layers: analytics, interpretation, and synthesis. You’ll learn how the same data point can yield multiple—and sometimes contradictory—conclusions depending on how it’s framed and combined with other information. We’ll break down the differences between descriptive and diagnostic analytics, but more importantly, we’ll show how data interpretation is the hidden force shaping every decision you make—and the critical gap standing between you and better product outcomes.
While all three components—analytics, interpretation, and synthesis—are important, interpretation is the most influential:
→ Analytics reveals what is there
→ Interpretation determines what it means
→ Synthesis connects it to what else we know
You can have perfect data and flawless analytics, but if the interpretation is off, the conclusions—and outcomes—will be too.
Interpretation is what introduces judgment, context, bias, and meaning into the system. It’s where decisions begin to take shape.
At the core of this session is the SCOPE framework: Spot, Compare, Orient, Probe, Execute—a powerful tool for interpreting and reconciling data across use cases.
You’ll learn:
Why flawless analytics still lead to bad decisions
How smart PMs make meaning—not just reports
A simple but powerful method to move from scattered signals to strategic clarity
By the end, you’ll walk away with a repeatable way to move beyond surface-level summaries into decisions grounded in nuance, context, and relevance.